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UNICEF Global Story

Breastfeeding and Child Survival

A Comprehensive Visualization and Analysis Project

Name: Drishti Pahwa
University: Dublin City University Name
Program: MSSM
Module: BAA1030 Data Analytics and Storytelling
Submission Date: 27 April 2025

1 Introduction

Breastfeeding is a critical pillar for child survival, yet global disparities persist.
This project explores breastfeeding rates and under-5 mortality across countries, using advanced interactive visualizations to uncover patterns, trends, and actionable insights.

2 Executive Summary

Breastfeeding saves lives.
This project visualizes global patterns in breastfeeding rates and under-5 child mortality,
highlighting urgent gaps and recommending actionable strategies to improve child survival worldwide.

3 Dataset

Code 
import polars as pl
import pandas as pd
import geopandas as gpd
import plotly.express as px
from plotnine import *

unicef_1 = pl.read_csv('unicef_indicator_1.csv', infer_schema_length=10000)
unicef_2 = pl.read_csv('unicef_indicator_2.csv', infer_schema_length=10000)


shape_world = gpd.read_file(
    "https://public.opendatasoft.com/api/explore/v2.1/catalog/datasets/world-administrative-boundaries/exports/geojson"
)

4 Global Breastfeeding and Mortality Map

Code 
bf_data = (
    unicef_2.filter(pl.col("indicator").str.to_lowercase().str.contains("breastfeeding"))
    .filter(pl.col("country").is_not_null())
    .group_by("country")
    .agg(pl.col("obs_value").mean().alias("breastfeeding_rate"))
)
bf_df = pd.DataFrame(bf_data.to_dicts())

mortality_data = (
    unicef_1.filter(pl.col("indicator").str.to_lowercase().str.contains("mortality"))
    .filter(pl.col("country").is_not_null())
    .group_by("country")
    .agg(pl.col("obs_value").mean().alias("under5_mortality_rate"))
)
mortality_df = pd.DataFrame(mortality_data.to_dicts())

merged_df = pd.merge(bf_df, mortality_df, on="country", how="inner")


fig = px.choropleth(
    merged_df,
    locations="country",
    locationmode="country names",
    color="breastfeeding_rate",
    hover_data=["breastfeeding_rate", "under5_mortality_rate"],
    color_continuous_scale=px.colors.sequential.Tealgrn,
    title="Global Breastfeeding Rates and Under-5 Mortality"
)

fig.update_geos(projection_type="natural earth")
fig.update_layout(
    paper_bgcolor='#e6f2ff',
    plot_bgcolor='#e6f2ff',
    margin={"r":0,"t":50,"l":0,"b":0}
)
fig.show()
Note

Insight:
Breastfeeding rates and child survival outcomes are deeply linked, especially in low-income regions. Countries in Sub-Saharan Africa and South Asia show strong breastfeeding performance,
while parts of Europe and North America lag surprisingly behind.

Recommendation:
Strengthen breastfeeding promotion within broader child healthcare systems globally.

5 Bottom 10 Countries by Breastfeeding Rate & Mortality Rate

Code 
bottom10 = bf_df.nsmallest(10, 'breastfeeding_rate')


fig = px.bar(
    bottom10,
    x="country",
    y="breastfeeding_rate",
    color="breastfeeding_rate",
    color_continuous_scale=px.colors.sequential.Peach,
    text_auto='.2f',
    title="Bottom 10 Countries by Breastfeeding Rate"
)

fig.update_traces(
    hovertemplate='Country: %{x}<br>Breastfeeding Rate: %{y:.1f}%',
    marker_line_width=1.5,
    marker_line_color='darkgrey'
)

fig.update_layout(
    paper_bgcolor='#e6f2ff',
    plot_bgcolor='#e6f2ff',
    hovermode="closest"
)
fig.show()
Note

Insight:
Barriers like cultural norms, misinformation, and lack of maternity support drive low breastfeeding rates. Smaller nations like Rwanda, Burundi, and the Solomon Islands lead the world, outperforming larger economies.
These results suggest that policy focus and community-level maternal education have a larger impact than GDP alone.

Recommendation:
Invest in education campaigns and supportive legislation for breastfeeding mothers.

6 Best vs Worst Countries

Code 
# Scatter Data
scatter_df = pd.concat([bf_df.nlargest(10, 'breastfeeding_rate'), bf_df.nsmallest(10, 'breastfeeding_rate')])
scatter_df = scatter_df.merge(mortality_df, on="country")

fig = px.scatter(
    scatter_df,
    x="breastfeeding_rate",
    y="under5_mortality_rate",
    hover_name="country",
    color="breastfeeding_rate",
    trendline="ols",
    color_continuous_scale=px.colors.sequential.Peach,
    title="Best vs Worst Countries: Breastfeeding vs Mortality"
)

fig.update_traces(
    marker=dict(size=12, opacity=0.8, line=dict(width=1, color='DarkSlateGrey'))
)

fig.update_layout(
    paper_bgcolor='#e6f2ff',
    plot_bgcolor='#e6f2ff',
    margin={"r":0,"t":50,"l":0,"b":0}
)
fig.show()
Note

Insight:
A clear negative relationship exists: higher breastfeeding rates = lower mortality rates. Generally, lower breastfeeding rates are associated with higher child mortality.

Recommendation:
Policy incentives should prioritize breastfeeding as a key child survival intervention. This suggests that improving maternal education, breastfeeding support programs, and healthcare access could significantly reduce preventable child deaths in

8 Conclusion

This project underlines the pivotal role breastfeeding plays in ensuring child survival worldwide. Efforts should prioritize education, healthcare access, maternity protection, and international cooperation to achieve SDG targets for child health by 2030.

Author: Drishti Pahwa | University: DCU

Module: BAA1030 Data Analytics and Storytelling | Submission Date: 27 April 2025